同源藥理揭示舊藥新用與蛋白質化合物交互作用網路

Abstract

開發新藥是相當耗時且昂貴。近幾年，舊藥新用成為加速治療方針進到臨床試驗的新方向。許多藥物被指出與多個標靶蛋白作用並應用在新的治療目標。開發同時抑制多標靶蛋白藥物可以增進治療效果，尤其是治療癌症等複雜疾病。因此如何有效辨別一小分子化合物的標靶蛋白將有助於舊藥新用與設計多標靶藥物，然而這仍是尚待解決的問題，因為許多標靶蛋白無法透過蛋白質序列或結構相似性來辨別。在此論文中，我們提出同源藥理概念 (Homopharma)，來描述分子介面中具保留性的結合環境與蛋白質與小分子化合物彼此的結合特性，並用來探討分子結合機制與舊藥新用。 同源藥理包含一群具有相似結合介面的蛋白質與有相似結構與功能單元的小分子化合物。為了找出具有保留性的結合介面，我們發展空間相關藥理模板概念(Space-Related Pharma-motifs, SRPmotif)，利用藥理介面與空間不連續藥理模板針對結構資料庫快速搜尋相似結合環境。結果顯示具有相似藥理介面的蛋白質不僅有相似的細胞反映路徑，也表現相似的生物功能。同一同源藥理中蛋白質與小分子化合物具有一致的交互作用與相似的物理化學特性，因此這些小分子化合物能與同源藥理中蛋白質結合。實驗結果也證明同一同源藥理中蛋白質與小分子化合物複合體具有由保留性胺基酸(蛋白質)與重要功能單元(小分子化合物)所構成相似的交互作用。 根據同源藥理概念，我們從酵素實驗檢測中成功發現56組全新類黃酮與蛋白激酶抑制效果(IC50 ≤ 10 μM)，其中25組抑制效果更達到小於1 μM。在這些發現中，部分抑制效果顯示測試的類黃酮衍伸物可用於治療如口腔癌或大腸癌等的抗癌藥物。這些結果顯示同源藥理概念不僅可辨識蛋白質與小分子間重要結合環境，更可用於發現舊藥的新用途。此外為了設計更具選擇性的蛋白激酶抑制劑，我們也建立蛋白激酶-抑制劑-疾病家族地圖(KIDFamMap)資料庫，藉由探索蛋白激酶抑制劑家族與蛋白激酶－抑制劑－疾病間關聯性來研究蛋白激酶抑制劑選擇性與結合機制。同一蛋白激酶抑制劑家族中的蛋白激酶－抑制劑交互作用經常在特定的錨點位置顯現一致性，這些錨點描述蛋白激酶子區域與激酶抑制劑共同功能單元間產生一致性交互作用特性。結果顯示同一蛋白激酶抑制劑家族中成員具有相似的抑制模式。 結合同源藥理概念、小分子化合物對蛋白質抑制效果與疾病相關資料，我們可以建構一個以結構為主的蛋白質化合物交互作用網路，並藉此了解蛋白質－化合物¬－疾病間關聯性。透過此網路不僅對辨識藥物潛在的標靶蛋白、改進藥物效用與了解藥物毒性有所助益。更進一步，它更能針對特定疾病提供新的治療方針。我們相信在本論文中所提出的概念將可幫助生物學家了解分子間結合機制，並對舊藥新用與藥物開發提出新的契機。

Developing a new drug is extremely time consuming and expensive. Recently, repurposing drugs or pro-drugs has been proposed as an important paradigm for accelerating therapeutic strategies into clinical trials. Many drugs have been indicated that they can interact with more than one target protein and been used for new indications. In addition, drugs that simultaneously target multiple proteins often improve efficacy, particularly in the treatment of complex diseases such as cancers. Therefore, how to identify target proteins of a compound will be helpful for drug repurposing and multi-target drug design. However, it is still an unsolved problem because many target proteins are not similar in their sequences or structures. In this thesis, we propose the core concept "Homopharma", which describe the conserved binding environment and preferred properties between proteins and compounds, to explore the molecular binding mechanisms and drug repurposing. A Homopharma consists of a set of proteins with the conserved binding interface and a set of compounds that share similar structures and functional groups. In order to recognize the conserved binding interfaces, we developed Space-Related Pharma-motifs (SRPmotif) composed of pharma-interfaces and discontinuous pharma-motifs to rapidly search similar binding interfaces against the structure database. Our results show that proteins of the identified pharma-interfaces not only are involved in the similar cellular process, but also perform similar biological functions. Furthermore, the proteins and compounds in a Homopharma share conserved interactions and similar physico-chemical properties; therefore, the compounds can often bind to the proteins. Experimental results show that protein-compound complexes of a Homopharma often preform similar interactions in which formed by conserved binding residues (protein sites) and similar important functional groups (compound sites). According to the Homopharma concept, we successfully discovered 56 novel flavonoid-kinase inhibitions (IC50 ≤ 10 μM) by in vitro enzymatic profiling, whereas the IC50 values of 25 bioassays are less than 1 μM. Some novel flavonoid-kinase inhibitions also suggest that these flavonoids can be considered as potential anticancer compounds such as oral and colorectal cancer drugs. The results indicate that Homopharma can be utilized to recognize key binding environments between proteins and compounds and discover new usages for existing drugs. Moreover, to design selective kinase inhibitors, we also developed KIDFamMap to explore kinase-inhibitor families (KIFs) and kinase-inhibitor-disease relationships for kinase inhibitor selectivity and mechanisms. The kinase-inhibitor interactions of a KIF are often conserved on some consensus KIDFamMap anchors, which represent conserved interactions between the kinase subsites and consensus moieties of their inhibitors. Our results reveal that the members of a KIF often possess similar inhibition profiles. Integrating the concept of Homopharma, inhibitory effects of compounds, and diseases information, a structure-based protein-compound interaction network can be constructed to explore protein-compound-disease relationships. This protein-compound interaction network would not only be helpful for identifying additional targets of repositioning drugs, improving efficacy and understanding toxicity of compounds, but also provides opportunities for revealing new therapeutic strategies of specific diseases. We believe that these concepts proposed in this thesis can have the potential for understanding molecular binding mechanisms and giving new clues for drug repurposing and drug development.